Dynamic Vehicle Routing with Parking Probability under Connected Environment

In downtown areas of large cities, it is very challenging for drivers to find available parking spots, even when they are provided with information on parking availability and location information. To overcome this challenge, this paper develops a dynamic vehicle routing system to search for the optimal routes for connected vehicles to find parking spots successfully and to minimize total trip time, including driving time and walking time. The system predicts the probability of each parking lot having available parking spots based on the existing available number of spots and the vehicle arrival and departure rates collected by connected vehicles. This probability is integrated in the search for vehicle routes to minimize total travel and walking times. Numerical experiments indicate that the proposed system can reduce the cruising time spent searching for available parking spots, and the total trip time can be reduced by up to 24%. In addition, the system can decrease the number of re-routing decisions, which reduces the stress of drivers on the road. A sensitivity analysis of the parking probability is also conducted. Some future work based on the proposed system is proposed in the conclusion to this paper.